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Perceiving the world in terms of objects and tracking them through time is a crucial prerequisite for reasoning and scene understanding.
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Evaluating multiple object tracking performance: The clear mot metrics
Keni Bernardin and Rainer Stiefelhagen · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Scikit-learn: Machine learning in Python
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Domenico Daniele Bloisi and Luca Iocchi · 2012
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
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Diederik P Kingma and Max Welling · 2014
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Volodymyr Mnih, Nicolas Heess, Alex Graves, and Koray Kavukcuoglu · 2014
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Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge · 2015
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Max Jaderberg, Karen Simonyan, Andrew Zisserman, and Koray Kavukcuoglu · 2015
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Diederik P. Kingma and Jimmy Ba · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Attend, infer, repeat: Fast scene understanding with generative models
S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, and Geoffrey E Hinton · 2016
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Tagger: Deep unsupervised perceptual grouping
Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hao, Harri Valpola, and Jürgen Schmidhuber · 2016
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MOT16: A benchmark for multi-object tracking
A. Milan, L. Leal-Taixé, I. Reid, S. Roth, and K. Schindler · 2016
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Neural expectation maximization
Klaus Greff, Sjoerd van Steenkiste, and Jürgen Schmidhuber · 2017
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Deep feature consistent variational autoencoder
X. Hou, L. Shen, K. Sun, and G. Qiu · 2017
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Tracking by animation: Unsupervised learning of multi-object attentive trackers
Zhen He, Jian Li, Daxue Liu, Hangen He, and David Barber · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Mots: Multi-object tracking and segmentation
Paul Voigtlaender, Michael Krause, Aljosa Osep, Jonathon Luiten, Berin Balachandar Gnana Sekar, Andreas Geiger, and Bastian Leibe · 2019
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Unsupervised discovery of parts, structure, and dynamics
Zhenjia Xu, Zhijian Liu, Chen Sun, Kevin Murphy, William T. Freeman, Joshua B. Tenenbaum, and Jiajun Wu · 2019
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Generative modeling of infinite occluded objects for compositional scene representation
Jinyang Yuan, Bin Li, and Xiangyang Xue · 2019
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Categorical reparameterization with gumbel-softmax
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Building machines that learn and think like people
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dsprites: Disentanglement testing sprites dataset
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Mind games: Game engines as an architecture for intuitive physics
Tomer D. Ullman, Elizabeth Spelke, Peter Battaglia, and Joshua B. Tenenbaum · 2017
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Object perception
Scott P Johnson · 2018
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Sequential attend, infer, repeat: Generative modelling of moving objects
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Alignnet: Unsupervised entity alignment
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Unsupervised object-centric video generation and decomposition in 3D
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Object-centric learning with slot attention
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Entity abstraction in visual model-based reinforcement learning
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